AIMC Topic: Neoplasm Recurrence, Local

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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non-muscle-invasive Bladder Cancer.

European urology oncology
Despite being standard tools for decision-making, the European Organisation for Research and Treatment of Cancer (EORTC), European Association of Urology (EAU), and Club Urologico Espanol de Tratamiento Oncologico (CUETO) risk groups provide moderate...

The usefulness of CanAssist breast in the assessment of recurrence risk in patients of ethnic Indian origin.

Breast (Edinburgh, Scotland)
Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach...

Oncologic Outcomes of Intracorporeal Extracorporeal Urinary Diversion After Robot-Assisted Radical Cystectomy: A Multi-Institutional Korean Study.

Journal of endourology
We aimed to compare the oncologic outcomes of intracorporeal urinary diversion (ICUD) and extracorporeal urinary diversion (ECUD) following robot-assisted radical cystectomy (RARC) in patients diagnosed with bladder cancer. Medical records of 730 p...

Radiomics-based neural network predicts recurrence patterns in glioblastoma using dynamic susceptibility contrast-enhanced MRI.

Scientific reports
Glioblastoma remains the most devastating brain tumor despite optimal treatment, because of the high rate of recurrence. Distant recurrence has distinct genomic alterations compared to local recurrence, which requires different treatment planning bot...

Oncologic Equipoise Between Robotic and Open Radical Cystectomy.

Journal of endourology
Our objective was to establish the incidence of positive surgical margins, recurrence patterns, and recurrence-free (RFS) and overall survival (OS) in a large cohort of patients undergoing robotic (robot-assisted radical cystectomy [RARC]) and open ...

A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants.

BMC biology
BACKGROUND: Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been succe...

An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
INTRODUCTION: Liver transplantation (LT) is an effective treatment for hepatocellular carcinoma (HCC), the most common type of primary liver cancer. Patients with small HCC (<5 cm) are given priority over others for transplantation due to clinical al...

Machine learning-based prediction model using clinico-pathologic factors for papillary thyroid carcinoma recurrence.

Scientific reports
This study analyzed the prognostic significance of clinico-pathologic factors, including the number of metastatic lymph nodes (LNs) and lymph node ratio (LNR), in patients with papillary thyroid carcinoma (PTC), and attempted to construct a disease r...

Prediction of Recurrence in Patients with Stage III Colon Cancer Using Conventional Clinicopathological Factors and Peripheral Blood Test Data: A New Analysis with Artificial Intelligence.

Oncology
BACKGROUND: Survival rate may be predicted by tumor-node-metastasis staging systems in colon cancer. In clinical practice, about 20 to 30 clinicopathological factors and blood test data have been used. Various predictive factors for recurrence have b...